Brian O'Connor   UBCO Psychology   UBCO  

A First Steps Guide To The Transition From Null Hypothesis Significance Testing To More Accurate And Informative Bayesian Analyses


O'Connor, B. P. (2017). A first steps guide to the transition from null hypothesis significance testing to more accurate and informative Bayesian analyses. Canadian Journal of Behavioral Science, 49(3), 166-182.


This article begins with a brief summary of the problems with null hypothesis significance testing (NHST), followed by a short, nontechnical description of perhaps the most useful NHST alternative, Bayesian methods. Simple R commands and output for Bayesian correlations, regressions, and ANOVA are provided. This is followed by examples of how to describe Bayesian analyses in the Methods and Results sections of articles. The focus is on taking the cautious first steps in a transition away from NHST.

Click here for the R code and output for the Bayesian data analyses that were described in the above article:

The links below provide R code and output for Bayesian analyses of the example datasets that are used in the following textbook:

Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. Los Angeles, CA: Sage.

The R code below was produced in collaboration with Dylan Ermacora.


R code

R output

Chapter 6: Correlation

Ch6_Correlation.R Ch6_Correlation.txt

Chapter 7: Regression

Ch7_Regression.R Ch7_Regression.txt

Chapter 8: Logistic Regression

Ch8_Logistic.R Ch8_Logistic.txt

Chapter 9: Comparing two means

Ch9_Two_Means.R Ch9_Two_Means.txt

Chapter 10: Comparing several means (ANOVA)

Ch10_ANOVA.R Ch10_ANOVA.txt

Chapter 11: Analysis of covariance


Chapter 12: Factorial ANOVA

Ch12_Factorial_ANOVA.R Ch12_Factorial_ANOVA.txt

Brian P. O'Connor
Department of Psychology
University of British Columbia - Okanagan
Kelowna, British Columbia, Canada